Context Engineering Kit is a collection of skills, agents, hooks, instructions, commands, and plugins that shape how coding agents use context and carry out development work. It is for developers using Claude Code and other supported coding agents who want more predictable results. The catalogue entries are components from this collection.
Getting it into your agent
One page per mod, every tool's command on it. A separate URL per tool would split the same page into five that compete with each other.
npx agentmods add skills/neolabhq/context-engineering-kit/memorizenpx skills add NeoLabHQ/context-engineering-kit --skill memorizegit clone --depth 1 https://github.com/NeoLabHQ/context-engineering-kitWrote this? Show the measurements
A badge with what this costs and how it scanned, read live from this page, so it follows the numbers instead of freezing them. Markdown for a README, HTML for a documentation site or a project page.
[](https://agentmods.dev/skills/neolabhq/context-engineering-kit/memorize)<a href="https://agentmods.dev/skills/neolabhq/context-engineering-kit/memorize"><img src="https://agentmods.dev/badge/skills/neolabhq/context-engineering-kit/memorize.svg" alt="Measured on agentmods" height="20"></a>What it costs to keep this loaded
Counted locally with the o200k_base tokenizer, which is exact for GPT models; Claude uses its own tokenizer and its counts differ. Treat this as one consistent yardstick across the catalogue rather than a bill. Prices are per million input tokens.
| Model | Per session | Once invoked |
|---|---|---|
| Fable 5.1 | $0.00020 | $0.02391 |
| Opus 5 | $0.00010 | $0.01196 |
| Sonnet 5 | $0.00004 | $0.00478 |
| Haiku 4.5 | $0.00002 | $0.00239 |
Grade A, and why
memorize scanned grade A with 0 findings against 26 rules in 11 categories — prompt injection, anti-refusal, data exfiltration, privilege escalation, supply chain, agent snooping, system-prompt leakage, SSRF and excessive agency — measured 2d ago.
A static scan of the body, not an audit. Every finding is printed with the line that produced it so you can judge whether it matters here. A mod is markdown that instructs an agent; that is exactly why what it instructs is worth reading.
Nothing flagged
None of the 26 patterns this scan looks for appear in this file: no shell pipes, no recursive deletes, no credential paths, no hidden text, no instruction-override or anti-refusal phrasing, no agent-config snooping. That is not a guarantee, it is the absence of the things that are checkable.
The source is not reproduced here
Licensed GPL-3.0
The repository is licensed GPL-3.0, which this catalogue does not treat as permission to reproduce the file. Read it at the source.
What this file has done since we first saw it
Hashed on every crawl. A supply-chain change to an agent config is a question of when, not whether, so the history is kept rather than the latest state alone.
- 2d ago First seen · 303 lines · 20 tokens per session scan A fcfcf036a3e9
memorize is a skill published in the GitHub repository NeoLabHQ/context-engineering-kit (1,541 stars, last pushed 10d ago), licensed GPL-3.0. It adds 20 tokens to every session and 2,391 once invoked, about $0.0001 per session on Opus 5. A static security scan graded it A with 0 findings. No closer match exists in the catalogue, so it is treated as the original; first seen 2026-09-03.
Other skills, from other repositories
a2wave-memory
Progressively recall and maintain a2wave cross-session memory through a compact startup catalog, bounded topics, and searchable history.
memoryguard
Local-first MCP memory backend and governance console for coding agents. Auto-organize, quarantine, supersede, and rollback shared memories across multiple agents.
review-claude-code
Claude Code setup review (settings.json, permissions, rules, hooks, agents, memory, worktrees) against current official best practices. USE WHEN: user runs /review-claude-code or explicitly asks for this review. DO NOT USE WHEN: reviewing app code, other dev dependencies, or implementing features.
learning-retrospective
Use when a task just succeeded after multiple failed attempts or a non-obvious workaround (capture the lesson), when you are re-encountering a problem that a stored lesson already covers, when you have repeated the same failed action verbatim, or when the user asks for a retrospective or lesson to prevent future retry…
memory-extraction
Agent-only workflow for extracting key information from conversations, code changes, and deployments into structured memory files. Automatically updates omp/memory/ directory and notifies other agents. Triggered automatically at conversation end or when valuable information is detected.
memory_progressive_disclosure
3-layer search protocol that minimizes token waste when querying persistent memory.